A Novel Hybrid Spotted Hyena Optimizer: An Algorithm for Fuel Consumption Capacitated Vehicle Routing Problem

Abstract

Distribution activities are closely related to the objective function of minimizing fuel consumption, which is affected by distance and product load in transportation. This indicates the need for optimization to improve company performance. Therefore, this study aims to develop a new Hybrid Spotted Hyena Optimizer (HSHO) algorithm, to minimize the total transportation and fuel costs. This was provided by applying the Large Rank Value (LRV) procedure to convert hyena positions to travel sequences. This also proposed a Flip and Swap rule in each iteration to improve the algorithm's performance. Furthermore, a mathematical model was developed for the Fuel Consumption Capacitated Vehicle Routing Problem (FCCVRP) by considering the load and FC (fuel consumption) rates between the nodes. This indicated that several population variations, iterations, and several nodes were used to investigate the effectiveness of the HSHO algorithm. The results showed increased population parameters, and HSHO iterations reduced the FCCVRP total transportation costs. Furthermore, decreasing the fuel consumption rate between nodes affected reduced fuel consumption. In addition, the proposed HSHO produced a more optimal total transportation cost than the state-of-the-art algorithm.